Video tracking is the process of locating a moving object (or multiple objects) over time using a camera (or other image capturing device). Video tracking has a variety of uses, some of which include: security and surveillance; human-computer interaction; video communication and compression; augmented reality; traffic control; medical imaging; and video editing. Video tracking can be a time-consuming process due to the amount of data that is contained in video. Adding further to the complexity is the possible need to use object recognition techniques for tracking.
Typically, the objective of video tracking is to associate target objects in consecutive video frames. The association can be difficult when the objects are moving fast relative to the frame rate. Another situation that increases complexity of the problem is when the tracked object changes orientation over time.
Matching is an important component of the video tracking process in which part (or all) of a query image is matched to a part (or all) of another image. One general example is to match one image patch with a second image patch. A more specific example is to match one or more objects with one or more image patches in a query image. The object may be a person (or a part of a person, such as a face), a thing (such as an inanimate object), or the like.
One example of video tracking is illustrated in FIG. 1, which shows a simple example of image tracking a single object. In the present example depicted in FIG. 1, object A has been reliably tracked over three frames (shown to the left in FIG. 1). In the fourth frame, which is referred to as the query frame, the goal is to locate the image patch (shown in shading in FIG. 1) that corresponds to the object. In a more general scenario, there may be multiple objects that are matched and located in the query frame, and their corresponding image patches can overlap significantly. To add to this complexity, there can be lighting and appearance variation of an object from frame to frame. All this makes the task of matching a challenging problem. Therefore, a need exists to efficiently and accurately perform video tracking.